3. Multiple regression analysis of model index rows of widths, temperature and precipitation with intention to reveal the limiting factors for growth, type and localities;

4. Identification of stress periods (SP) for individual species and localities – periods with It < 1 and of stress sections – In;

5. Characteristic of identified In to find the most reliable stress-sections (intervals of years for various localities and types)– calculation of indicators of In: duration (D), amplitude (A) and frequency (F) – average and extreme values, coverage (Cov.) and cardinality (Card.) of stress sections. Stress sections with Cov. ≥ 50% take part in the analysis;

6. Polynomial approximation of climate data for temperatures and rainfall, and selection of the best approximation. Calculation of Itm, Ip;

7. Finding the average temperatures and rainfall for 30 – year periods, and the confidence interval of the average climatic and biological climate years by localities. Calculating of av.T, dT, av. P and dP;

8. Determination of adverse climatic and biological climatic years – AHD, AHW, ACD, ACW in both regimes and different combinations in which one of the regimes is normal according to the dT and dP;

9. Parallel analysis of stress periods and climate data. Comparative analysis of the periods of stress sections with adverse years;

10. Storing the results in a database;

11. Adding optional features to perform separate analysis;

12. Adding features for a graphical representation of the analysis results.